Embedding Nearest Neighbors

Find the k nearest neighbors of a query word in an embedding space using cosine similarity.

Input format:

• Line 1: The query word and k (space-separated)
• Line 2: Number of words N
• Lines 3 to N+2: word followed by its embedding vector

Output: List of k nearest words (excluding the query), sorted by descending cosine similarity. Print as a Python list of strings.